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---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: AraBERT_token_classification__AraEval24_truncated_rand
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# AraBERT_token_classification__AraEval24_truncated_rand
This model is a fine-tuned version of [aubmindlab/bert-base-arabert](https://huggingface.co/aubmindlab/bert-base-arabert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0021
- Precision: 0.1263
- Recall: 0.1171
- F1: 0.1215
- Accuracy: 0.5544
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 479 | 1.7309 | 0.0864 | 0.0189 | 0.0310 | 0.5847 |
| 1.6653 | 2.0 | 958 | 1.6503 | 0.0855 | 0.0393 | 0.0539 | 0.5793 |
| 1.3608 | 3.0 | 1437 | 1.6761 | 0.1075 | 0.0579 | 0.0753 | 0.5869 |
| 1.1267 | 4.0 | 1916 | 1.7633 | 0.1003 | 0.0786 | 0.0882 | 0.5442 |
| 0.9119 | 5.0 | 2395 | 1.7995 | 0.1050 | 0.0877 | 0.0956 | 0.5442 |
| 0.783 | 6.0 | 2874 | 1.8613 | 0.1151 | 0.0937 | 0.1033 | 0.5607 |
| 0.6667 | 7.0 | 3353 | 1.9148 | 0.1155 | 0.1061 | 0.1106 | 0.5472 |
| 0.5967 | 8.0 | 3832 | 1.9480 | 0.1267 | 0.1175 | 0.1219 | 0.5511 |
| 0.5397 | 9.0 | 4311 | 1.9909 | 0.1235 | 0.1126 | 0.1178 | 0.5487 |
| 0.4948 | 10.0 | 4790 | 2.0021 | 0.1263 | 0.1171 | 0.1215 | 0.5544 |
### Framework versions
- Transformers 4.30.2
- Pytorch 1.12.1
- Datasets 2.13.2
- Tokenizers 0.13.3
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